Abstract. One of the fundamental factors contributing to the spatiotemporal inaccuracy in climate modeling is the mapping of solution field data between different discretizations and numerical grids used in the coupled component models. The typical climate computational workflow involves evaluation and serialization of the remapping weights during the pre-processing step, which is then consumed by the coupled driver infrastructure during simulation to compute field projections. Tools like Earth System Modeling Framework (ESMF) Hill et al. (2004) and TempestRemap Ullrich et al. (2013) offer capability to generate conservative remapping weights, while the Model Coupling Toolkit (MCT) Larson et al. (2001) that is utilized in many production climate models exposes functionality to make use of the operators to solve the coupled problem. However, such multi-step processes present several hurdles in terms of the scientific workflow, and impedes research productivity. In order to overcome these limitations, we present a fully integrated infrastructure based on the Mesh Oriented datABase (MOAB) Tautges et al. (2004); Mahadevan et al. (2015) library, which allows for a complete description of the numerical grids, and solution data used in each submodel. Through a scalable advancing front intersection algorithm, the supermesh of the source and target grids are computed, which is then used to assemble the high-order, conservative and monotonicity preserving remapping weights between discretization specifications. The Fortran compatible interfaces in MOAB are utilized to directly link the submodels in the Energy Exascale Earth System Model (E3SM) to enable online remapping strategies in order to simplify the coupled workflow process.We demonstrate the superior computational efficiency of the remapping algorithms in comparison with other state-of-science tools and present strong scaling results on large-scale machines for computing remapping weights between the spectral-element atmosphere and finite-volume discretizations on the polygonal ocean grids.

Accurate climate modeling of coupled earth systems require mapping of solution field data between dependent components that use non-matching discrete meshes. While existing workflows provide a pathway to generate the projection weights as an offline step, severe bottlenecks impede flexible setup of high resolution models. In this paper, we present new algorithmic approaches to simplify the E3SM computational workflow using a scalable software infrastructure to generate the remapping operators.